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Abstract Background: Social determinants of health (SDOH) are critical drivers of cancer care access and outcomes. In multiple myeloma (MM), access to cellular therapies including autologous stem cell transplantation and CAR-T therapy often depends on formal or informal caregiver support. Traditional SDOH measures (e.g., race, income, or education) are often used as proxies for access to care; however, these measures may overlook individual realities pertaining to cellular therapies where a caregiver is generally required. In response to feedback from a HealthTree Patient Advisory Board questioning the practice of inferring caregiver support, this study evaluated a simple survey question by a large cross-sectional survey. Methods: After development of a dedicated single-question (“What best describes your current caregiving support?”) through iterative feedback from the Patient Advisory Board and MM experts, four key answers were settled on: (1) cohabitation with dedicated caregiver(s) to support care (“family support”); (2) presence of non-cohabiting caregiver(s) to provide dedicated support (“external support”); (3) lack of dedicated caregiver, hence support is arranged when needed (“arrangeable support ”); or (4) lack of dedicated caregiver, hence finding any support is a struggle (“inadequate support”). We deployed this new demographic question from February through July 2025 through HealthTree. Responses were analyzed across SDOH variables using Fisher exact or chi square tests, and random forest classifiers were employed for predictive modeling. Results: Of 1231 respondents, 71% had dedicated caregivers (68%, n=839, with family support, and 3%, n=41, with external support). In contrast, 23% (n=287) of patients routinely arranged support while 5% (n=64) had inadequate support (struggle to find support). The inadequate-support group had significant demographic differences from the sample as a whole: a higher proportion were women (78% vs 56%, p = 0.04), Black (9% vs 4%, p < 0.01), lived >50 miles from their treatment center (17% vs 6%, p < 0.01), and had an annual income <$50,000 (17% vs 6%, p = 0.02). This group had a numerically higher proportion of patients whose employment status was disabled (12% vs 5%, p=0.08) as well. No proportion difference in age (67 ± 9 yr), military status, or severity of diagnosis - precursor disease (17%) v. multiple myeloma (81%). Rates of inadequate support were overall low in patients who lived with only their spouse (1%) or lived with their spouse & children (3%). In contrast, rates of inadequate support were higher (than 5%) in patients who lived alone (21%), divorced (20%), lived with adult children (14%), lived with friends (13%), separated (11%), or widowed (9%) (p < 0.001). However, the arrangeable-support group comprised 12% of patients who lived only with their spouse, 19% of patients who lived with their spouse and children, and 61% of patients who lived with their adult children (p < 0.001). Finally, a random forest classifier failed to identify any individual in the inadequate-support category, suggesting that unmeasured or more complex patterns may underlie this classification. Conclusions: To our knowledge, this is the largest analysis of caregiver support and its relationship with other SDOH in patients with MM to date. Despite the importance of caregiving to transplantation and CAR-T therapy, we found that 5% of patients with MM struggle to find caregiver support; this figure likely underestimates the true prevalence, given potential selection bias among patients who are digitally engaged through the HealthTree platform. Even among patients who lived with their spouses, an additional 10-20% of patients routinely had to arrange caregiving support on a visit-by-visit basis; for patients who lived with their adult children, this proportion was over 60%. The requirement to arrange caregiving support can create time toxicity and financial toxicity for patients, although these factors were not directly queried in our study. Finally, caregiver availability cannot be routinely inferred from traditional SDOH variables. Our data highlight the importance of including caregiver status as a standard demographic question in clinical and research settings. Further interventions are needed to improve caregiver support for vulnerable patients with MM as well as to reduce the duration of caregiver requirements for procedures such as CAR-T therapy.

Abstract Somatic mutations in hematopoietic stem and progenitor cells (clonal hematopoiesis) are known to alter the immune milieu and can result in autoimmune disorders including VEXAS (Vacuoles, E1 enzyme, X-linked, Autoinflammatory, Somatic) syndrome. There are currently no curative strategies for CH-linked autoimmune disorders besides allogenic hematopoietic stem cell transplantation. Recent work has shown a high prevalence of autoimmune syndromes among patients with IDH1/2 mutant myeloid neoplasms (MN). We thus hypothesized that IDH1/2-mutant CH might drive a subset of autoimmune disorders. To further characterize a possible association between IDH-mutant CH and autoimmune disease, we used data from two observational cohort studies, the UK Biobank (N=454,218) and All of Us (N=414,830). We observed 264 individuals with IDH1/2-mutant CH. IDH1/2 CH was associated with autoimmune disease (OR=1.8, p=4e-3), and, when compared to other CH genes with at least 100 carriers, showed the strongest effect size. When comparing autoimmune subtypes, we observed significant associations with polymyalgia rheumatica (OR=4.0, p=1e-3) and giant cell arteritis (OR=8.1, p=1e-6). IDH1/2 CH carriers had elevated CRP levels compared to other CH-carriers (p=1e-2) and non-carriers (p=8e-3). IDH1/2 CH was associated with lower neutrophil counts and higher monocyte counts. While most (68%) had blood counts outside the normal range, only a minority (11%) had severe cytopenias that met criteria for CCUS. Since IDH1/2 CH is associated with both autoimmune disease and blood count abnormalities, we sought to define the frequency, clinical presentation, and outcomes of IDH1/2-associated autoimmune disease among individuals with bone marrow biopsy confirmed CCUS. We used data from three CCUS cohorts: first, a multi-institutional cohort of CCUS patients with systemic autoinflammatory disease (SAID) who were UBA1-negative, second, a hospital-based cohort at Mayo Clinic, and third, a cohort of IDH1 carriers enrolled on a phase II clinical trial of ivosidenib (NCT05030441). Within 193 SAID patients who were free of myeloid neoplasm at the time of recruitment, IDH1/2 pathogenic variants were the most observed CH driver, occurring in 2% of individuals. These individuals (N=4) all had recurrent fevers and dermatologic manifestations, requiring chronic glucocorticoid treatment with 75% having inflammatory arthritis requiring multiple Disease-Modifying Antirheumatic Drugs (range 1-7, median=5). Within the Mayo Clinic cohort, 275 patients with CCUS were serially ascertained. Among those 8 (2.9%) were IDH1-mutant of whom 50% had autoimmune disease (three with seronegative rheumatoid arthritis and one with Sweet syndrome). At last follow up (median 16 months), 2 (25%) of 8 patients had progressed to MN. Within our open-label decentralized trial of ivosidenib (IDH1 inhibitor) in CCUS, we enrolled 20 patients, of whom 5 (25%) had a diverse array of pre-existing autoimmune disorders, including two cases of seronegative rheumatoid arthritis and one case each of Sweet syndrome, polymyalgia rheumatica, and Sjögren's syndrome. Underlying the clinical presentation of all five cases was episodic joint pain, with half also experiencing episodic dermatologic manifestations. The majority (58%, 11/19) of the IDH1mt-CCUS patients had an elevated hsCRP (>=5; range 6.91–46.2) including all four with co-occurring autoimmune disorders (range 7.97–46.2). Out of the 20 enrolled patients, 17 received at least 8 weeks of therapy, of which 9 had elevated hsCRP at baseline. Most of these (7/9) had normalization of hsCRP (falling below 5 mg/L) while on treatment (median time to hsCRP normalization of 58 days). Among the four patients with autoimmune disease, all had subjective improvement in their autoimmune symptoms following treatment with ivosidenib. In conclusion, we show that IDH1/2 CH is associated with autoimmune disorders and is particularly enriched among IDH1/2 CH carriers with co-occurring cytopenias. IDH1/2-associated autoimmune disease can range from classic rheumatic conditions such as rheumatoid arthritis to more severe VEXAS like presentations. IDH inhibition demonstrates efficacy for improving inflammatory manifestations within an ongoing clinical trial. Together these results nominate IDH mutant CH as a driver of autoimmune diseases with therapeutic implications.

Abstract Outgrowth of a founder mutant clone is an initial event in leukemogenesis. The corresponding somatic hit likely conveys a fitness advantage over a polyclonal background. Several factors may modulate the competitiveness of hematopoietic stem or progenitor cells, including aging, genotoxic stress, repeated cycles of stress hematopoiesis, and inherited genetic fitness deficiency. The nature of these conditions provides a particularly fertile environment in which only certain mutant clones thrive. For instance, chemotherapy facilitates expansion of PPMD1MT or TP53MT clones, aging-related loss of fitness predisposes to outgrowth of TET2MT clones, while many inherited bone marrow failure (BMF) syndromes are associated with specific clonal acquisitions due to somatic gene rescue. Identification of factors enabling the expansion of clones with specific mutations may help to develop targeted preventive, screening, or therapeutic strategies. Recently, high levels of erythropoietin (EPO) induced by frequent blood donation were shown to favor the emergence of DNMT3AR882 clones due to their increased EPO sensitivity1. We theorized that this may be a more general phenomenon operating in other diseases characterized by high EPO levels. Thus, we selected 644 patients in whom endogenous serum EPO levels had been assessed and who underwent mutational NGS analysis. Given that this cohort consisted of patients with hematologic neoplasms, EPO levels were broad with the majority falling outside the normal clinical reference range. For this study we used EPO levels ≥100mU/mL as the threshold to define high and low EPO groups. This threshold laid above the 75th percentile for our cohort (M=31.1; IQR=109.7) to capture outliers more likely to reflect biologically significant erythropoietic stress. DNMT3AMT were present in 14% of high EPO and in 12% of low EPO groups (p=0.5). However, in the high EPO group, R882 constituted 32% of DNMT3AMT while in the low EPO group R882 was found in only 11% of DNMT3AMT cases (p=.02). In a reverse fashion, the mean level of EPO in DNMT3AR882 was 441.7mU/mL while it was 215.3mU/mL in other DNMT3AMT carriers (p=0.03) and 186.2mU/mL in DNMT3AWT cases (p<0.001). To assess whether the effect on DNMT3A was dependent on EPO levels rather than anemia, we determined mean hemoglobin levels in R882 (µ=10.2g/dL), other DNMT3AMT (µ=10.4g/dL), and wild type cases (µ=10.9g/dL) and found no significant differences (p=0.33). To assess whether R882-EPO sensitivity was related to EPO-R expression levels, we compared EPO-R expression in R882 (µ=2.7), non-R882 (µ=2.6) mutations, and WT cases (µ=2.8) and found no significant difference. To assess whether the impact of high EPO states was specific to DNMT3AMT we next analyzed the distribution of other mutations. We observed that frameshift mutations in BCOR (p = 0.013) and BCORL1 (p=0.036) were significantly more frequent in high EPO patients. BCORMT was also overall more prevalent in the high EPO group (p=.001), while BCORL1 frequency was similar across EPO strata (p=0.77) showing a similar trend to DNMT3AMT. Beyond these genes, other patterns emerged, particularly within CH-associated genes. Individuals with U2AF1MT had elevated EPO (p=.0087), with variant-specific enrichment: p.S34F was more common in high EPO (p=.038) whereas p.Q157P predominated in low EPO patients (p=0.038). No significant EPO associations were observed for other CH-related genes such as ASXL1, CBL, and TET2. The limitations of this study notwithstanding, these findings support a biologically meaningful relationship between elevated EPO levels and the acquisition or enrichment of specific CH-associated mutations in patients with hematologic malignancies. The association of high EPO with DNMT3AR882, frameshift mutations in BCOR/L1, and variant-specific enrichment in U2AF1 suggests that EPO-driven stress may contribute to clonal selection or expansion. Our study of high EPO levels and DNMT3AMT analysis illustrates that external conditions may influence selection pressure for specific mutations. However, selection pressure may be a complex combination of factors. Non-malignant conditions with high EPO, such as hypoxia or intrinsic BMF, may also create conditions facilitating the acquisition of specific somatic hits. Recognition of evolutionary pressures and their associations with specific mutations may improve our understanding of CH pathogenesis, and conceptualization of therapeutic or preventative measures.

Abstract Background: Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disorder caused by PIGA mutations, resulting in complement-mediated hemolysis. Myeloproliferative neoplasms (MPNs) are also clonal hematopoietic stem cell disorders driven by mutations in JAK2, CALR, or MPL, and include polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). Although the coexistence of PNH and and MPN is rare, both entities are associated with anemia and an increased risk of thrombosis. The main objectives of the current study were to characterize the clinical phenotype, and evaluate treatment outcomes, including response to complement inhibition in patients with treatment-requiring PNH and MPN. Methods A Mayo Clinic database search was conducted following Institutional Review Board approval to identify patients with PNH and MPN. Between January 2000 and June 2025, 11 patients had a pathologic diagnosis of MPN per the International Consensus Classification, and PNH requiring therapy. Clinical features, including hemolysis and/or thrombosis, and therapeutic interventions were recorded. Results The study cohort included 11 patients (median age 63 years; 73% male) with MPN (6 with PMF, 3 ET, 1 post-ET MF, 1 post-PV MF) in whom PNH was diagnosed concurrently (n=5), or at a median of 9 years (range: 2-15) after MPN diagnosis (n=6). In 9 of 11 patients (82%), PNH workup was initiated due to hemolytic anemia, while in 2 patients (18%), it was prompted by splanchnic vein thrombosis. Transfusion-dependent anemia was present in 6 patients (54%). PNH clone size [median (range)] was 0.58% (0–10.96%) in red blood cells, 18.82% (0–91.2%) in granulocytes, and 23.27% (0–98.8%) in monocytes. MPN driver mutations were evaluated in 8 cases and identified mutations in JAK2 (n=3), CALR (n=4), and MPL (n=1); two additional cases were negative for JAK2 mutations. Next-generation sequencing (NGS) was performed in 6 patients and identified ASXL1, ZRSR2, and SF3B1 mutations in one case each. Cytogenetic analysis (n =10) demonstrated an abnormal karyotype in 3 patients (30%), all of which were categorized as favorable risk. First-line treatment for PNH included complement inhibitors in 9 patients (82%), with eculizumab (n=8), or ravulizumab (n=1). Hemolysis was controlled in only 2 of 9 (22%) patients; one patient treated with eculizumab achieved durable anemia response for five years, while another patient achieved transfusion-independence within three months of eculizumab initiation. 3 patients underwent allogeneic stem cell transplant (ASCT); 2 achieved remission with follow up exceeding 5 years, while the third patient experienced PNH recurrence five months after transplant. The latter received donor lymphocyte infusions and eculizumab was re-initiated resulting in eradication of the PNH clone. Among patients treated with complement inhibitor and not transplanted, 4 of 6 (67%) were transfusion-dependent at last follow-up. Notably, one patient with PNH clone size of 91.19 % in granulocytes, had ongoing hemolysis despite dual complement blockade with ravulizumab and danicopan. Treatment for MPN included hydroxyurea (n=5), ruxolitinib (n=4), pacritinib (n=1), and erythropoiesis stimulating agents (n=4). Additionally, two patients each received antiplatelet therapy alone, anticoagulation alone, or a combination of antiplatelet and anticoagulation. During a median follow-up of 8.4 years (range, 0.6-19), 2 patients (18%) experienced venous thrombosis, and 1 patient (9%) had progression to myelodysplastic syndrome. 5 patients (45.5%) died, with sepsis as the cause of death in 3 cases. The incidence rate of thrombosis was 22 events per 1,000 person-years. Recurrent thrombosis was observed in a 68-year-old male with CALR-mutated MF and PNH clone size of 14.65% in granulocytes, with history of portal vein thrombosis. Despite treatment with eculizumab and low-molecular weight heparin, he developed thrombosis involving the inferior vena cava, common iliac, and hepatic veins. The second event occurred in a patient who developed deep venous thrombosis, while in remission and not on anticoagulation. Conclusion The current study represents the largest series of patients with treatment-requiring PNH and MPN. It reveals a predominance of MF patients, particularly among those harboring CALRmutations, and underlines suboptimal efficacy of complement inhibitor therapy in this patient population.

Abstract The importance of bone marrow (BM) microenvironment and its immune interactions within and their role in chronic myelomonocytic leukemia (CMML) disease progression have not been well studied. Our previous work in CMML identified type 1 helper T cell (Th1) and CD4 terminal effector cell suppression in peripheral blood from untreated patients, in comparison to age-matched normal controls (Mangaonkar A et al. Blood Adv 2020). Furthermore, clonal dendritic cell (DC) aggregates in CMML are present in approximately 20-30% patients at diagnosis, display significant cell heterogeneity (plasmacytoid DCs + myeloid DCs and other myeloid/immune cells), express indoleamine 2,3-dioxygenase-1 (IDO), associate with T regulatory cell (Treg) expansion, and transformation to AML [blast transformation or BT, Lucas N et al. Leukemia 2019, Mangaonkar A et al. Blood Adv 2020, and Mangaonkar A et al. Blood 2023 (abstract)]. The purpose of this study was to define the myeloid-immune cell interactions within the BM microenvironment critical for CMML progression to AML. To phenotypically identify cell types and their interactions within the CMML BM, we used single-cell type spatial omics through two distinct modalities on archival formalin-fixed paraffin-embedded (FFPE) BM biopsy specimens. Ten serial CMML samples at chronic phase [CP, n=5, median BM blast% 5 (2-15)] and at BT [n=5, median BM blast% 60 (25-74)] were used for both techniques. Spatial transcriptomics was conducted through GeoMx Digital Spatial Profiler (DSP) platform that uses UV-photocleavable, spatial-barcoded oligo probes to profile the whole transcriptome in defined regions of interest (ROI). CD123 (marker for DC-myeloid aggregates) immunofluorescence antibody was used to identify and segment ROI. 16-color flow cytometry was done to validate cell-specific expression. Spatial cellular phenotyping of immune cells on the same samples (serial cuts) was done through multiplex imaging by co-detection by indexing (CODEX) using 27 markers: CD31, Ki67, CD11b, CD20, CD44, Ecad, CD123, CD107a, CD8, CD11c, CD45RO, FoxP3, CD14, PDL1, CD56, CD68, CD163, PD-1, CD38, HLA-DR, CD4, IDO, CD45, PanCK, Na/K/ATPase, CD3e, and DAPI. CD8T+ cell anergy was demonstrated through CFSE cell proliferation assay. Benjamini-Hochberg correction was used to adjust for multiple hypotheses. After filtering poor quality ROIs [ROIs with total read count < 1000 were removed, ROIs with trim, stitch, alignment < 80% or saturation < 50% were removed], 3rd-quartile normalization [BiocGenerics (v. 0.48.1)] and batch correction [limma (v. 3.58.1)], we compared transcriptomics signatures between CD123+ and CD123- ROIs in all samples. Results showed that LIPA, SLC4A1, HBA2, TIMD4 and HMOX1 werethe top five genes upregulated in CD123+ areas. Among all gene transcripts, TIMD4 expression increased the most (Log2FC=0.6, P-value=8.79E-10, FC=1.52, FDR=1.68E-07) when CD123+ ROIs were compared between CMML-CP and CMML-BT serial samples, suggesting a biological relevance in disease progression. Previous work in metastatic peritoneal cancer has established that TIM-4 expressing macrophages suppress Th1/Th2 ratios and impair CD8+ T cell function (Chow A et al. Cancer Cell 2021). To confirm expression at the protein level, we used a multicolor flow cytometry panel and confirmed that TIM4 is expressed on macrophages (Lineage-negative, HLA-DR+, CD68+ cells) in independent CMML BM aspirate samples (n=3). Next, we conducted spatial phenotyping using CODEX on serial cuts from the same serial samples used for spatial transcriptomics. Anatomical co-localization of macrophages with leukemic cells, monocytes and T cells was visually inspected and confirmed. Cell-interaction analysis (after Benjamini-Hochberg correction) indicated that macrophages-monocyte, macrophage-leukemic cells, and macrophage-memory CD4+T cells were significantly (P<0.05) increased in CMML-BT versus CMML-CP. CD8T+ cell anergy was confirmed through a CFSE cell proliferation assay in untreated CMML PBMC samples. In conclusion, our data suggests that TIM4-expressing macrophages and their interactions with monocytes/monocyte precursors and immune cells within a DC aggregate create a protective leukemic stem cell niche and T cell tolerance, promoting blast transformation in CMML.

Abstract Background The expansion of hematopoietic stem and progenitor cells (HSPCs) in the bone marrow is universally associated with adverse outcomes and disease progression in all chronic myeloid neoplasms, to include chronic myelomonocytic leukemia (CMML). However, HSPCs are a heterogeneous cellular compartment and the impact of its composition on clinical outcomes remains poorly defined. Single cell RNA-sequencing (scRNA-seq) represents an optimal strategy to annotate cellular composition but no large clinically annotated scRNA-seq datasets are currently available. To address this, we have embarked to generate a clinically annotated 500 patient CMML scRNA-seq atlas from CD34+ enriched BMNCs to establish among the largest clinically and genetically annotated single cell references for any chronic myeloid malignancy. Here we report the interim analysis of 113 clinically annotated cases that demonstrates massive reshaping of HSPC composition that is independently a predictor of overall survival. Methods Single-cell RNA expression profiling was performed on 113 CD34-enriched CMML BMNC samples using 10x Genomics GEM-X Universal 3' Gene Expression v4 (4-plex) chemistry. Libraries were sequenced on NovaSeq S4 flow cells in two runs, and data were processed using Cell Ranger to generate gene expression matrices. A total of 502,659 single cells from 113 samples were processed using Seurat. The upper threshold for gene count was defined as the mean number of detected genes plus two standard deviations data normalization was performed using the log-normalization method. Batch correction and integration were conducted with Harmony to mitigate technical variation across pools. Descriptive statistics were used to tabulate clinical and genetic parameters. KM curves, log-rank test, and cox regression were used to calculate survival, test for statistical differences, and perform multivariate analysis, respectively. Results To derive high resolution cell annotations, we employed the SingleR algorithm using a large hematopoietic reference of over 300,000 single cells (Zhang, X. Nature Immunology, 2024). Using this approach a diverse set of cell types were identified that included HSCs, 23 myeloid progenitors, 18 erythroid progenitors, and 18 lymphoid progenitors. This diverse cellular repertoire displayed massive reshaping relative to the normal CD34 enriched reference including a >53x expansion of multilineage GMPs and a >100x depletion of B-cell progenitors consistent with the known myeloid skewing seen in this disease. To understand whether expansion of specific progenitors was associated with outcomes we iteratively evaluated key progenitor populations and observed that expansions of HSC (HR 0.468 p<0.005) and MEP (HR 0.485, p<0.005) were associated with improved survival while GMP (HR 1.729, p=0.029) expansions were associated with inferior survival when using a cut point derived with a maximally selected ranks statistics approach. To achieve a more comprehensive metric of HSPC composition we explored GMP ratios to include GMP/HSC ratios and GMP/MEP ratios and observed that both were associated with inferior survival in univariate and multivariate when considering clinical and genetic features such as the CPSS-molecular prognostic score and FAB classification. When considering both GMP/HSC and GMP/MEP ratios in a multivariate model only GMP/MEP ratios and CPSS molecular remained independently prognostic. As an orthogonal approach, pseudotime projections were carried out using a reference map from Setty et al., 2019 to calculate differentiation potential and branch probabilities. This approach enabled both cell identity assignment and placement of cells along the hematopoietic differentiation trajectory. Samples were classified as monocyte-biased, MEP-biased, or normal-like, as previously described (Ferrall-Fairbanks et al. 2022) and demonstrated that increased GMP ratios are associated with a monocytic biased trajectory and that this trajectory is also associated with overall survival. Conclusion This study represents an interim analysis of among the largest scRNA-seq cohorts generated in chronic myeloid malignancies. This enabled us, for the first time, to demonstrate that HSPC composition is independently prognostic even when considering modern CMML prognostic models. As this cohort continues to increase, validation of these findings and examining the impact of therapy on HPSC composition in serial samples will be prioritized.

Abstract Background Blast transformation (BT) occurs in approximately 15-30% of patients with chronic myelomonocytic leukemia (CMML) and remains a leading cause of death. Allogeneic stem cell transplantation (ASCT) is currently the only treatment modality with the potential to cure the disease or prolong survival. Optimal timing of ASCT is critical for maximizing benefit while minimizing risks. To that end, contemporary risk models have focused on the prognostic relevance of individual, as opposed to concurrent mutations. In the current study, we looked into the possibility of prognostic prominence from concurrent mutations in predicting BT in CMML. Methods CMML diagnostic criteria were according to the International Consensus Classification (Arber et al. Blood 2022; 140:1200). A machine-learning hierarchical clustering algorithm was developed and tailored for patient stratification using survival outcomes and co-expression of genomic alterations. To reduce complexity and improve interpretability, we generalized each cluster using existing rule induction algorithms, including the in Trees framework and JRip. The final output was a set of mutation-based cluster definitions, each representing a distinct patient subgroup with similar survival trajectories. Competing risk analysis and cumulative incidence functions were used in downstream evaluation to validate the clinical distinctiveness of the clusters. For all survival analysis, patients were censored at the time of ASCT. Time-to-BT was calculated from the date of diagnosis to the date of BT or ASCT or last contact. BT-free-survival was calculated from the date of diagnosis to the date of BT, ASCT, death, or last contact. Results The core study cohort included 605 patients from the Mayo Clinic, USA, and the external validation cohort 501 patients from Humanitas Cancer Center, Milan, Italy. Using the patient cohort from the Mayo Clinic, machine-learning algorithms identified five molecular clusters with 3-year blast transformation (BT) rates ranging from 0% to 100% (AUC at 3 years 0.78): the order of molecular signature assignment (probability of BT/death from another cause) was i) PHF6MUT/ASXL1WT (0%/17% at 3 years; N=32), ii) NPM1MUT OR BCORMUT/ASXL1MUT OR SETBP1MUT/NRASMUT (48%/30% at 1 year; N=24), iii) RUNX1MUT/ASXL1MUT OR SRSF2MUT/NRASMUT OR EZH2MUT/ASXL1MUT OR SETBP1MUT OR BCORMUT (31%/55% at 3 years; N=132), iv) ASXL1MUT/TET2MUT OR DNMT3AMUT OR JAK2MUT (24%/28% at 3 years; N=123), and v) all other permutations (10%/40% at 3 years; N=294) [Figure 1]. Additional analysis confirmed significant differences in survival between RUNX1MUT/ASXL1MUT vs. RUNX1MUT/ASXL1WT (p<0.01) OR RUNX1WT/ASXL1WT (p<0.01) OR RUNX1WT/ASXL1MUT (p=0.038) [Figure 2]. Similar patterns of differences in survival were also documented for NRAS/SETBP1, ASXL1/EZH2, and NRAS/SRSF2 mutation combinations (Figure 2). A subsequent Cox regression analysis confirmed independent prognostic contributions from “PHF6MUT/ASXL1WT” (HR 5.43e-10; p<0.01), NPM1MUT (HR 26.7; p<0.01), “SETBP1MUT/NRASMUT” (HR 12.7; p<0.01), BCORMUT(HR 5.8; p<0.01), “RUNX1MUT/ASXL1MUT” (HR 2.3, p<0.01), JAK2MUT (HR 2.1; p<0.01), and “ASXL1MUT/TET2MUT” (HR 1.7; p=0.02). The prognostic relevance of “SETBP1MUT/NRASMUT”, “RUNX1MUT/ASXL1MUT”, NPM1MUT, and BCORMUT was validated in the external cohort from Italy (N=501). In the Mayo Clinic cohort, presence of any of the latter mutations was associated with 1-, 3-, and 5-year BT (death from other cause) rates of 27% (21%), 44% (49%), and 44% (51%), respectively (Figure 3). The corresponding values in the absence of high risk mutations were 7% (15%), 15% (37%), and 18% (52%) [Gray's p value <0.01 for both BT and death from another cause; Figure 3]. Similarly, the 1-, 3-, and 5-year BT (death from another cause) rates in the Italian cohort were 21% (19%), 37% (47%), and 42% (54%) in the presence and 8% (14%), 20% (35%), and 24% (45%) in the absence of high-risk mutations (Gray's p value <0.01 for BT and 0.18 for death from another cause; Figure 4). Conclusions In the current study, machine-learning algorithms enabled the discovery of concurrent mutations in CMML that were shown to be prognostically more significant than their individual constituents. Such prognostic interaction might have contributed to some of the discrepancies noted in current literature regarding the prognostic relevance of certain mutations in CMML and should be accounted for in the development of future risk models.

Abstract Introduction Defining the epidemiology of myelodysplastic syndromes/neoplasms (MDS) and precursor conditions, such as clonal cytopenia of undetermined significance (CCUS), is challenging due to inconsistent reporting, complex diagnostics, and evolving criteria. The National MDS Natural History Study (NHS) overcomes these challenges through central pathology review, prospective follow-up, and a nationally representative cohort enrolled at the time of suspected MDS, enabling robust analysis across the myeloid disease spectrum. We analyzed clinical, genetic, and pathologic features in NHS participants by race, ethnicity, and sex to characterize disease variation across populations. Methods The NHS (NCT02775383) enrolled individuals undergoing evaluation for suspected MDS from June 2016–July 2024 at 102 US sites. Participants underwent bone marrow assessment with centralized, adjudicated histopathology review. Those meeting WHO 2016 criteria for MDS, MDS/myeloproliferative neoplasm (MPN), CCUS, idiopathic cytopenia/dysplasia of undetermined significance (ICUS/IDUS), or oligoblastic AML were followed longitudinally. Demographics, comorbidities, exposures, and clinical data were collected at baseline and every 6 months. Deep DNA sequencing was performed on baseline marrow, with pathogenic variants manually curated (53 genes). Statistical analyses assessed associations using chi-squared, Fisher's exact, Kruskal-Wallis, logistic regression, and Cox models. A p-value <0.05 was considered significant. Results Among 2,021 participants, 1,174 (58%) were diagnosed with MDS or precursor conditions. Median age was 74 years (yrs) and 66% were male. Most identified as Non-Hispanic White (NHW, 92%), with 4% Black and 4% Hispanic. The most common diagnoses were MDS (42%) and CCUS (37%). Pathogenic somatic mutations were identified in 84% (774/918) of MDS/CCUS, with TET2 (26% of 918), DNMT3A (21%), and ASXL1 (16%) most frequent. Median follow-up was 1.8yrs and consistent across race, ethnicity, and sex (p≥0.6). Black, compared to NHW, participants were younger (69 vs 74 yrs, p=0.006) and trended toward more females (47% vs 34%, p=0.09) and more MDS diagnoses (51% vs 41%, p=0.07). Black participants showed more advanced disease (e.g., lower hemoglobin, higher peripheral blood blasts, higher variant allele frequencies (VAFs) of pathogenic mutations), yet received less MDS-directed treatment (14% vs 41%, p=0.01). Black, compared to NHW, participants had more mutations in RUNX1, TP53, BCOR, and DNMT3A, but fewer in TET2 and ASXL1. Hispanic, compared to Non-Hispanic, participants had fewer known pathogenic mutations, leading to more ICUS (19% vs 5%, p=0.02). Females, compared to males, were younger at diagnosis (72 vs 75yrs, p<0.001), had more ICUS/IDUS (20% vs 10%, p<0.001), fewer pathogenic mutations, especially in splicing/chromatin modifier genes (U2AF1, SRSF2, ASXL1, ZRSR2), more DNMT3A mutations, and lower VAFs (0.27 vs 0.33, p<0.001). Median overall survival (OS) was 6.4yrs, and shorter in MDS (4.2yrs) than CCUS (not reached). Worse OS was associated with age (adjusted hazard ratio (aHR) 1.06), MDS (vs CCUS; aHR 1.89), higher-risk disease by IPSS-R/CCRS (aHR 2.15), and TP53 mutations (aHR 2.17) (all p<0.001). A trend toward improved OS in Black participants was attenuated after adjustment (aHR 0.79, p=0.6). Progression (e.g., worsening of disease, increase in transfusion dependency, death) occurred in 53% of participants. Worse progression-free survival (PFS) was associated with MDS diagnosis (aHR 2.59), higher-risk disease by IPSS-R/CCRS (aHR 2.17), and TP53 mutations (aHR 1.86) (all p<0.001). Despite more advanced disease and less MDS therapy, Black participants trended toward improved PFS (aHR 0.62, p=0.14), while age was borderline significant (aHR 1.01, p=0.05). Conclusions For the first time, we show that among individuals evaluated for suspected MDS at sites across the US, 58% had MDS or precursor conditions. Differences across demographics underscore the heterogeneity of MDS. Black participants presented with more advanced MDS, received less treatment, but trended toward improved outcomes, particularly PFS, even after adjustment, suggesting biological rather than access-to-care differences driving disparities. These findings highlight the complex interplay of sex, race, and genetics in shaping MDS outcomes and reinforce the need for diverse, large-scale studies to improve risk stratification and personalized care.

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p<0.001) but higher frequencies than MDS (p<0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p<0.001) but lower than in MD-CMML (p<0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (>94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (>94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p<0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.

Abstract Introduction: Standardized reporting of clinical trials results for MDS is essential to improve clinical interpretation and cross-study comparison. However, reporting of patient characteristics, response criteria, and endpoints in publications is often inconsistent; there is no systemic analysis of MDS trial reporting available. We conducted a systematic review of published MDS trial manuscripts on behalf of the international consortium for MDS (icMDS) to assess variability in reporting practices. Methods We searched ClinicalTrials.gov to identify all clinical trials registered for adults (≥18 years) with MDS that reported results between 2015-2024. Clinical trials that included acute myeloid leukemia (AML) or MDS/myeloproliferative neoplasms (MPN) were included if they enrolled ≥5 MDS patients. We excluded trials without an MDS cohort; non-therapeutic trials; trials focused on transplant interventions; or those which enrolled solid malignancies or other hematologic malignancies (chronic myeloid leukemia or lymphoid diseases). Finally, trials were required to have a manuscript available on Larvol, PubMed, or Google Scholar. Trials were categorized by disease risk (lower-risk [LR] vs. higher-risk [HR]) and trial phase (early phase [EP] vs. late phase [LP]). Results We identified 502 MDS trials on ClinicalTrials.gov, of which 351 did not meet inclusion criteria and 79 lacked a manuscript. A total of 72 trials (32 EP, 40 LP) with 80 publications (34 EP, 46 LP) were analyzed. Frequently reported baseline characteristics included age (100% EP, 100% LP), disease risk (74% EP, 74% LP), Eastern Cooperative Oncology Group performance status (85% EP, 72% LP), prior treatments (71% EP, 67% LP), and RBC transfusion dependency (32% EP, 70% LP). Less frequently reported characteristics included blood counts (hemoglobin [Hb; 38% EP, 54% LP], platelet count [38% EP, 54% LP], neutrophil count [24% EP and LP]) and bone marrow blasts (29% EP, 43% LP). Although disease risk was widely reported, definitions varied: IPSS and IPSS-R were each reported in 54% of manuscripts, while IPSS-M appeared in only 3%. Cytogenetic risk was separately reported in 39% of manuscripts (38% EP, 39% LP), and mutational data in 45% (47% EP, 43% LP). Responses per IWG 2006 criteria were reported in 84% of manuscripts. The primary endpoint involved safety/tolerability in 85% of EP manuscripts, though definitions were variable; recommended phase 2 dose was the most common (26% of EP manuscripts). In LP trials, primary endpoints were risk-specific: transfusion independence (TI) in 77% of LR, overall response rate (ORR) in 28% of HR, and complete remission (CR) or overall survival (OS) in 22% of HR. In HR manuscripts, CR was reported in 100%, ORR in 73%, hematologic improvement (HI) in 48%, RBC-TI in 23%, and OS in 80%. However, seven different definitions were used for ORR: CR + marrow CR + partial remission + HI per IWG 2006 was most common (35%). Event-free survival was reported in 25%; progression-free survival and relapse-free survival in 13%; and leukemia-free survival in 5%. Early mortality rate was reported in 35% (18% EP, 56% LP) and transplant rate in 58% (50% EP, 67% LP). Only 47% of HR and 90% of LR manuscripts identified HI-eligible patients. In LR-MDS, RBC-TI was reported in 72% of manuscripts but used six definitions. The most common were RBC-TI ≥8 weeks at any time during treatment (24%), ≥8 weeks within 28 weeks of treatment (13%), ≥8 weeks with Hb increase ≥1.0 (4%), ≥12 weeks with Hb increase ≥1.5 (4%), and ≥16 weeks within 24 weeks of treatment (12%). The remainder did not report RBC-TI, did not define it, or used a custom definition not used in another trial. HI was reported in 80% of LR papers with most of those reporting HI using IWG 2006 criteria (90%). Conclusion Reporting of baseline characteristics, response criteria, and outcomes is inconsistent in MDS clinical trials, with wide variability in response definitions, including ORR and TI. This heterogeneity limits interpretability, hampers historical comparisons and may obscure efficacy signals. Our findings highlight the need for standardized reporting guidelines to ensure clarity and consistency in MDS trial publications. As a next phase of this effort, we will conduct a formal Delphi process among icMDS experts to establish consensus recommendations for minimal and optimal MDS clinical trial reporting in manuscripts by disease risk (LR/HR) and trial phase (EP/LP).